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» Using Machine Learning to Focus Iterative Optimization
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109
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ICPR
2010
IEEE
15 years 5 months ago
Feature Selection Using Multiobjective Optimization for Named Entity Recognition
Appropriate feature selection is a very crucial issue in any machine learning framework, specially in Maximum Entropy (ME). In this paper, the selection of appropriate features for...
Asif Ekbal, Sriparna Saha
162
Voted
ML
1998
ACM
153views Machine Learning» more  ML 1998»
15 years 2 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
CVPR
2010
IEEE
15 years 11 months ago
Boundary Learning by Optimization with Topological Constraints
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by mini...
Viren Jain, Benjamin Bollmann, Bobby Kasthuri, Ken...
128
Voted
ICML
2009
IEEE
16 years 3 months ago
Partially supervised feature selection with regularized linear models
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
Thibault Helleputte, Pierre Dupont
126
Voted
COLT
2000
Springer
15 years 6 months ago
Leveraging for Regression
In this paper we examine master regression algorithms that leverage base regressors by iteratively calling them on modified samples. The most successful leveraging algorithm for c...
Nigel Duffy, David P. Helmbold